Factors influencing discrepancies in self-reported memory and performance on memory recall in the Canadian Community Health Survey-Healthy Aging, 2008-09

Self- and Partner-Reported Subjective Memory Complaints: Association with Objective Cognitive Impairment and Risk of Decline

Background

Episodic memory decline is a hallmark of Alzheimer's disease (AD). Subjective memory complaints (SMCs) may represent one of the earliest signs of impending cognitive decline. The degree to which self- or partner-reported SMCs predict cognitive change remains unclear.

Objective

We aimed to evaluate the relationship between self- and partner-reported SMCs, objective cognitive performance, AD biomarkers, and risk of future decline in a well-characterized longitudinal memory center cohort. We also evaluated whether study partner characteristics influence reports of SMCs.

Methods

758 participants and 690 study partners were recruited from the Penn Alzheimer's Disease Research Center Clinical Core. Participants included those with Normal Cognition, Mild Cognitive Impairment, and AD. SMCs were measured using the Prospective and Retrospective Memory Questionnaire (PRMQ), and were evaluated for their association with cognition, genetic, plasma, and neuroimaging biomarkers of AD, cognitive and functional decline, and diagnostic progression over an average of four years.

Results

We found that partner-reported SMCs were more consistent with cognitive test performance and increasing symptom severity than self-reported SMCs. Partner-reported SMCs showed stronger correlations with AD-associated brain atrophy, plasma biomarkers of neurodegeneration, and longitudinal cognitive and functional decline. A 10-point increase on baseline PRMQ increased the annual risk of diagnostic progression by approximately 70%. Study partner demographics and relationship to participants influenced reports of SMCs in AD participants only.

Conclusion

Partner-reported SMCs, using the PRMQ, have a stronger relationship with the neuroanatomic and cognitive changes associated with AD than patient-reported SMCs. Further work is needed to evaluate whether SMCs could be used to screen for future decline.

Identifying Patient Readmissions: Are Our Data Sources Misleading?

BACKGROUND

The accuracy of data is vital to identifying hospitalization outcomes for clinical trials. Patient attrition and recall bias affects the validity of patient-reported outcomes, and the growing prevalence of Medicare Advantage (MA) could mean Fee-for-Service (FFS) claims are less reliable for ascertaining hospital utilization. Statewide health information exchanges (HIEs) may be a more complete data source but have not been frequently used for research.

DESIGN

Secondary analysis comparing identification of readmissions using 3 different acquisition approaches.

SETTING

Randomized controlled trial of heart failure (HF) disease management in 37 skilled nursing facilities (SNFs).

PARTICIPANTS

Patients with HF discharged from the hospital to SNF.

MEASURES

Readmissions up to 60 days post-SNF admission collected by patient self-report, recorded by nursing home (NH) staff during the SNF stay, or recorded in the state HIE.

RESULTS

Among 657 participants (mean age 79 ± 10 years, 49% with FFS), 295 unique readmissions within 60 days of SNF admission were identified. These readmissions occurred among 221 patients. Twenty percent of all readmissions were found using only patient self-report, 28% were only recorded by NH staff during the SNF stay, and 52% were identified only using the HIE. The readmission rate (first readmission only) based only on patient self-report and direct observation was 18% rather than 34% with the addition of the enhanced HIE method.

CONCLUSIONS AND IMPLICATIONS

More than one-quarter (34%) of HF patients were rehospitalized within 60 days post SNF admission. Use of a statewide HIE resulted in identifying an additional 153 admissions, 52% of all the readmissions seen in this study. Without use of an HIE, nearly half of readmissions would have been missed as a result of incomplete patient self-report or loss to follow-up. Thus, HIEs serve as an important resource for researchers to ensure accurate outcomes data.